238 Hauer et al.: Assessment of Tree Debris Following Urban Forest Ice Storms significance level and none were found (Mertler and Vannatta 2005). Assumptions of normality, linearity, and homoscedastic- ity were tested using bivariate plots between independent and dependent variables, a plot of the standardized residuals and standardized predicted values from the final multiple regression model, and Box’s Test for Equality of Covariance Matrices. The variance inflation factor (VIF) statistic was used to test for mul- ticollinearity and this was interpreted as occurring with a VIF ≥ 10 (Neter et al. 1990; Mertler and Vannatta 2005). Tulsa, Okla- homa, U.S., was identified as an extreme value, and two final models were created (Mertler and Vannatta 2005). The Tulsa data were considered an extreme location based on the much larger size of the community and volume of debris generated relative to other communities in the model. The Tulsa data were compa- rable to other locations when debris volumes were normalized by community area or street distance and compared to other study sites. Creating separate models is an accepted way to account for an extreme case that likely reflects a valid observation (Mertler and Vannatta 2005). Two cases (Springfield, Missouri and Saint Louis, Missouri, U.S.) were removed after initial modeling and casewise diagnostics indicated these as outliers based on the residual exceeding three standard deviations. A third normal- ized model (debris volume per community infrastructure attri- bute) was developed and no study sites were found as outliers. RESULTS Survey Response There were 298 communities targeted in 15 states with potential ice storm data. A total 132 communities responded (44% response rate) with 71 (54%) of these reporting ice storms while the remain- ing 61 (46%) had not encountered any ice storms since January 1, 2000. However, of the 71 communities that had ice storms, only 60 returned usable data. Several communities that were unable to respond provided reasons including an inability to locate the Table 1. Descriptive statistics from all model communities (n = 40). Variables Minimum From Questionnaire Land area (km2 ) Street distance (km) Public debris (m3 Private debris (m3 Total debris (m3 Total debris (m3 Total debris (m3 Total debris (m3 Total debris (m3 Ice thickness (cm) ) ) ) /km2 )z /km)y /km2 /cm)x /km/cm)w Max. wind speed (km/h) From NLCD Nowak (2010) Population year 2000 (#) Pop. density 2000 (#/km2 Total land area (km2 Canopy cover (%) ) ) Developed land area (km2 Developed land area (%) z Total debris/land area y Total debris/street distance x Total debris/land area/ice thickness w Total debris/street distance/ice thickness ) 5.2 8.5 42.1 38.2 76.5 2.7 0.5 2.1 0.6 0.4 4.8 707.0 172.4 2.1 3.3 0.7 28.6 Maximum 468.8 6,964 273,963 107,038 2,140,754 5,719.1 1,129 2,055 208.5 12.7 64.4 393,049 2,171 473.2 51.2 341.8 97.8 data, staff changes, small community with few staff, and/or not enough labor to follow through with the debris estimations and recording at the time of the storm. Some communities may have ice storm data, but indicated they were short of staff or that other job duties prevented them from completing the questionnaire. Of the 60 communities that responded, four communities completed two surveys (one per storm), thus 64 ice storms were reported. Model Data and Debris Volumes Estimation Pearson correlations coefficients suggested strong fits between debris volumes and all community infrastructure variables, which are street miles (0.909), total community land area (0.828), total 2001 NLCD land area (0.877), and developed land area (0.866). Simply put, the larger the area or street distance, the greater vol- ume of debris. No simple relationships were found for the urban forest weather (ice and wind) or structure attribute (canopy cover) and debris volumes. Proportionally adjusting (normalized) debris by street distance or land area resulted in strong correlations be- tween the volume of debris per street distance (0.616) and ice thickness or volume of debris per land area (0.534) and ice thick- ness. Negative correlations between wind speed and debris volume per land area per ice thickness (-0.373) and between wind speed and debris volume per street distance per ice thickness (-0.373) were detected. No significant relationship between canopy cover and nonnormalized or normalized debris volumes were found. Forty communities provided sufficient data (e.g., debris volume estimates, community infrastructure, weather param- eters) from an ice storm to include in the authors’ models. The mean debris collected was 145,218 m3 1). By street distance, this mean was 179.8 m3 area the mean was 1172 m3/km2 of debris reported by storm. Responding towns experienced a mean of 3.6 cm of ice thick- ness that was between 0.4 cm and 12.7 cm. The maximum wind speed during the ice storm was a mean 28.8 km/h with re- ported values between 5 km/h and 64 km/h. A few communi- Mean 73.8 602.2 30,700 20,636 145,218 1,172.4 179.8 365.4 51.8 3.6 28.8 55,749 771.4 67.3 17.4 47.1 68.8 Standard error of mean 15.4 182.7 13,221 7,787 60,301 259.6 42.3 75.6 9.6 0.5 2 13,971 64.7 14.6 2.1 10.8 3.1 Standard deviation 97.2 1,141 62,012 30,158 381,379 1,641.9 264.1 478.3 60.1 2.9 12.8 88,359 409.4 91.4 13.2 67.3 19 per ice storm (Table /km and by land ©2011 International Society of Arboriculture
September 2011
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